Hi there
I have been using R to perform kmeans on a dataset. The data is fed in using
read.table and then a matrix (x) is created
i.e:
[
mat <- matrix(0, nlevels(DF$V1), nlevels(DF$V2),
dimnames = list(levels(DF$V1), levels(DF$V2)))
mat[cbind(DF$V1, DF$V2)] <- DF$V3
This matrix is then taken and a distance matrix (y) created using dist() before
performing the kmeans clustering.
My query is this: not all the data for the initial matrix (x) exists and
therefore the matrix is not fully populated - empty cells are populated with
'0's.
Could someone please tell me how this may affect the result from the dist()
command - because a '0' in a distance matrix means that the two variables are
identical doesnt it(?) - but I dont want tthings clustered together simply
because there was no information.
Is this a problem and are there ways to circumnavigate them? Thanks
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